Forecasting yield and market classes of Vidalia sweet onions: A UAV-based multispectral and texture data-driven approach by Marcelo Rodrigues Barbosa Júnior, Lucas de Azevedo Sales, Regimar Garcia dos Santos, Rônega Boa Sorte Vargas, Chris Tyson, Luan Pereira de Oliveira

“…Yield stands as an important quantitative parameter, and market class emerges as an important quality factor. …”
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Unveiling psychobiological correlates in primary Sjögren’s syndrome: a machine learning approach to determinants of disease burden by László V. Módis, László V. Módis, András Matuz, András Matuz, Zsófia Aradi, Ildikó Fanny Horváth, Antónia Szántó, Antal Bugán

“…The five most important predictors were selected for all target outcomes.ResultsConcerning autoantibodies, the model performed best with biological input only, in the case of ESSPRI, the complete dataset gave the best performance. …”
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Assessment of synthetic post-therapeutic OCT images using the generative adversarial network in patients with macular edema secondary to retinal vein occlusion by Shi Feng, Jingyuan Yang, Xinyu Zhao, Jianchun Zhao, Yunfeng Du, Weihong Yu, Dayong Ding, Xirong Li, Youxin Chen

“…Evaluations conducted both qualitatively and quantitatively indicated that our model can generate high-quality post-therapeutic OCT images. …”
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Biomarker composition and origin of Miocene pale lignites in China and Serbia by Bangjun LIU, Jingzhi LI, Ksenija STOJANOVIĆ, Jiazhong HUANG, Yueting LIU, Yumeng SUN, Dragana ŽIVOTIĆ, Jinxi WANG, Yuzhuang SUN, Cunliang ZHAO

“…The results show that the pale lignite in Mile Basin has a high content of long-chain n-alkanes (up to 82.5%), showing a significant contribution from leaf waxes of terrestrial higher plants (mainly angiosperms), accompanied by a lower aquatic plant indicator value (Paq of 0.16) and a higher plant leaf wax index (Pwax of 0.86), indicating that its coal-forming environment was relatively dry and accompanied by strong microbial degradation; while the dark lignite has an increased proportion of medium-chain and short-chain n-alkanes, indicating that the input of aquatic plants and lower organisms was enhanced during the sedimentation process in Mile Basin. …”
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Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis by Mahreen Kiran, Ying Xie, Nasreen Anjum, Graham Ball, Barbara Pierscionek, Duncan Russell

“…Articles were qualitatively assessed on their alignment with T2DM prediction using a four-point relevance scale and quantitatively evaluated based on citation metrics normalized within subject, journal, and publication year. …”
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Navigating HOPE (Hypermobile Online Pain managemEnt): Perspectives and Experiences From People With Hypermobile Ehlers–Danlos Syndrome or Hypermobility Spectrum Disorder on a Condi... by Min Tze Chew, Emre Ilhan, Sarah Dennis, Leslie L. Nicholson, Sarah Kobayashi, Cliffton Chan

“…Patient or Public Contribution A large community of hEDS/HSD patients' and healthcare providers' input were obtained from a two‐staged online Delphi from a prior study. …”
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Deep Learning-Based Real-Time Driver Cognitive Distraction Detection by Matteo Fresta, Francesco Bellotti, Igor Bochenko, Luca Lazzaroni, Gaetan Merlhiot, Fabio Tango, Riccardo Berta

“…First, we assessed the effectiveness of state-of-the-art time series-oriented deep learning models in learning features from 60 Hz raw input signals, thus implementing an end-to-end machine learning approach, without manual feature engineering. …”
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Neural Network-Based Predictive Control of COVID-19 Transmission Dynamics to Support Institutional Decision-Making by Cristina-Maria Stăncioi, Iulia Adina Ștefan, Violeta Briciu, Vlad Mureșan, Iulia Clitan, Mihail Abrudean, Mihaela-Ligia Ungureșan, Radu Miron, Ecaterina Stativă, Michaela Nanu, Adriana Topan, Ioana Nanu

“…This research primarily focuses on designing a control technique that incorporates the five most important inputs that impact the spread of COVID-19 on the Romanian territory. …”
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Understanding the effectiveness and underlying mechanisms of lifestyle modification interventions in adults with learning disabilities: a mixed-methods systematic review by Dikshyanta Rana, Sophie Westrop, Nishant Jaiswal, Evi Germeni, Arlene McGarty, Louisa Ells, Phillippa Lally, Michael McEwan, Craig Melville, Leanne Harris, Olivia Wu

“…A patient and public involvement group provided input and insights throughout the project. Results A total of 80 studies with 4805 participants were included in the systematic review. …”
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A Patch-Level Region-Aware Module with a Multi-Label Framework for Remote Sensing Image Captioning by Yunpeng Li, Xiangrong Zhang, Tianyang Zhang, Guanchun Wang, Xinlin Wang, Shuo Li

“…Extensive qualitative and quantitative experimental results show the superiority of our approach on the RSICD, UCM-Captions, and Sydney-Captions. …”
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Density-Guided and Frequency Modulation Dehazing Network for Remote Sensing Images by Haijun Liu, Jiachen Huang, Jing Nie, Jin Xie, Lihui Chen, Xichuan Zhou

“…Furthermore, current approaches primarily address foggy inputs within the spatial domain, neglecting the potential advantages of exploring the frequency domain for dehazing. …”
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Development of channel transmission loss function for WRF_HYDRO modeling of semi-arid regions: The case of wadi Faria, Palestine by Abdelhaleem Khader, Anan Jayyousi, Sameer Shadeed, Joel Arnault, Harald Kunstmann, Christian Chwala, Benjamin Fersch

“…To address these challenges, hydrological modeling has been used to gain understanding of the hydro-logical systems and to provide the required inputs needed for sustainable water resources management. …”
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Stellar Population and Energy Feedback in the Supergiant Shell LMC 1 by Guan-Hong Li, Chuan-Jui Li, You-Hua Chu, Po-Sheng Ou, C.-H. Rosie Chen, Konstantin Grishunin, Hsu-Tai Lee

“…We have studied SGS LMC 1 to determine quantitatively whether stellar energy feedback is adequate to power the formation of an SGS. …”
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The influence of correlated features on neural network attribution methods in geoscience by Evan Krell, Antonios Mamalakis, Scott A. King, Philippe Tissot, Imme Ebert-Uphoff

“…Few studies have quantitatively analyzed the influence of correlated features on XAI attributions. …”
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Average direct cost of peripherally inserted central catheterization by nurses in hospitalized patients: a cost estimate by Maithê Gomes Lima Zandonadi, Danielly Negrão Guassú Nogueira, Amanda Salles Margatho do Nascimento, Paula Buck de Oliveira Ruiz, Natália Marciano de Araújo Ferreira, Suellen Karina de Oliveira Giroti, Flávia Meneguetti Pieri

“…Methods: A cost estimation study using a quantitative approach was conducted in a public teaching hospital in northern Paraná to calculate the direct costs of peripherally inserted central catheterization. …”
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Climate change awareness and the role of cashew plantations in mitigation and adaptation strategies in Ghana’s Savannah ecological zone by Eric Heinno Botir, Raymond Aabeyir, Justice Aduko, Francis Nangbeviel Sanyare

“…The data were analyzed using descriptive statistics and inductive thematic analysis for quantitative and qualitative data, respectively. The results show a high awareness of climate change (97.5%) among cashew farmers. …”
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The study on dynamic modeling and path planning of a manta ray-inspired underwater glider by Yi Zhang, Jianing Zhang, Zhiyang Guo, Lei Zhang, Yuchen Shang, Weimin Chen

“…A novel dynamic model for the gliding mode is developed, which takes the acceleration of a movable mass and the rate of change of a buoyancy control device as control inputs. Compared to previous methods, this model incorporates the real-time dynamic response of the control system, providing a more detailed depiction of the glider’s dynamic behavior. …”
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Controlling agricultural product price volatility: An empirical analysis from Cameroon by Ivette Gnitedem Keubeng, George Achu Muluh, Vatis Christian Kemezang

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PENC: a predictive-estimative nonlinear control framework for robust target tracking of fixed-wing UAVs in complex urban environments by Shiji Hai, Xitai Na, Zhihui Feng, Jinshuo Shi, Qingbin Sun

“…This framework optimizes the UAV-gimbal system’s control inputs in real-time to ensure the target remains within the camera’s field of view (FOV) despite obstacles, while simultaneously using historical target state measurements to accurately estimate its current state. …”
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Convolutional neural networks-based red blood cell detection and tracking with automatic data generation by Kohei TOYAMA, Tomoki MIZUNO, Takuto ARAKI, Toru HYAKUTAKE

“…Moreover, we used the difference image between consecutive frames, along with RBC images, as inputs for CNNs. We validated the detection accuracy and evaluated the hematocrit and flow rate results obtained using the proposed method for each channel during in vitro experiments. …”
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